Sobre o curso

>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<<
This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. We’ll learn about the fundamentals of Linear Algebra and Neural Networks. Then we introduce the most popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML. Keras and TensorFlow are making up the greatest portion of this course. We learn about Anomaly Detection, Time Series Forecasting, Image Recognition and Natural Language Processing by building up models using Keras on real-life examples from IoT (Internet of Things), Financial Marked Data, Literature or Image Databases. Finally, we learn how to scale those artificial brains using Kubernetes, Apache Spark and GPUs.
IMPORTANT: THIS COURSE ALONE IS NOT SUFFICIENT TO OBTAIN THE "IBM Watson IoT Certified Data Scientist certificate". You need to take three other courses where two of them are currently built. The Specialization will be ready late spring, early summer 2018
Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give your ideas for turbocharging successful creation and deployment of DeepLearning models. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this course will help serve as your guide.
Prerequisites: Some coding skills are necessary. Preferably python, but any other programming language will do fine. Also some basic understanding of math (linear algebra) is a plus, but we will cover that part in the first week as well.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging....

Melhores avaliações

RC

Apr 26, 2018

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It was really great learning with coursera and I loved the course. The way faculty teaches here is just awesome as they are very much clear and helped a lot while learning this coursea

BS

Aug 08, 2019

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Gave a good hands-on with IBM Watson studio notebooks. Also a good overview of LSTM's, Keras, Predictive maintenance. Good stuff, keep it going

Very intuitive course, helped me learn at my own pace, given that I was not having time at a stretch. I thoroughly enjoyed learning the concept and techniques of deep learning. Some of the exams were easy but the objective was that you continue learning, whille some were tough (where I learned the most). It was overwhelming to see real IoT data flowing through and reaching to my code :). Nice!!

It looks easy but simple things are "very" hard to produce so Thanks to the whole Team.

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por Freek W

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May 18, 2018

Good connection from the theory in Standford University: "Machine Learning" to modern day implementations of ML.

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por Muahammad U A

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May 20, 2018

This is best course in order to know how machine learning application is scaled on different machines.

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por A.Basit M

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May 08, 2018

nice

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por Rahul C

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Apr 26, 2018

It was really great learning with coursera and I loved the course. The way faculty teaches here is just awesome as they are very much clear and helped a lot while learning this coursea

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por Yibei

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Apr 29, 2018

I followed the course just fine and learned a lot.

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por Rudolf P

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Feb 24, 2018

This course provides deep insights, explanations and examples on how to apply deep learning networks to machine learning problems. The course level is intermediate - you will need some basic knowledge on deep learning and some programming skills in order to get most out of this course.

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por FRANCOIS K

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Jun 03, 2018

Overall very good course with experienced instructors and a main instructor whose enthusiasm is communicative. I have two modest improvement proposals. The oil price prediction assignment could be converted in an anomaly analysis - possibly in a Pytorch setting to deepen the initial presentation of Pytorch -, perhaps a more meaningful use of deep-learning to this time series data. Week 4 is a touch light compared to weeks 2 and 3 and could be improved by an assigment illustrating feedback between the anomaly signals in the IOT framework of week 3 and the IOT setup itself. Both anomaly and feedback would be deep-learning based.

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por Nikolas R

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Apr 14, 2019

The course covers a broad range of tools to deploy deep learning algorithms.

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por Saumya T

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Jun 02, 2019

Very good course for learning Neural Network. Well explained!!!

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por FREDDY Y

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Jun 06, 2019

great course

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por David J D T

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Jun 19, 2019

Would love to have a deeper lecture on NLP inside Watson

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por Neeraj k

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Jun 28, 2019

best method for understanding

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por Kylie T

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Jul 07, 2019

Very well organized course

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por Ashish P

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Jul 16, 2019

This is really Amazing Course. I learn those micro things which is people rarely understand.

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por Varadharajan R

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Aug 07, 2019

Self motivated to learn and do the assignments all the discussions in the forum guided me thoroughly

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por Bharath S

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Aug 08, 2019

Gave a good hands-on with IBM Watson studio notebooks. Also a good overview of LSTM's, Keras, Predictive maintenance. Good stuff, keep it going

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por Evan S

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Jun 15, 2019

I learned a lot about neural networks and the infrastructure they run on. I enjoyed the course very much.

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por 吴怡

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Aug 20, 2019

Wow, What a great course! This course really helps me understand the machine learning basis as well as the practical deployment in multiple environments and programming languages. Thanks for the lecturers and also Coursera!

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por Egemen İ

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Aug 28, 2019

This course and the knowledge it provided were incredibly helpful. Thank you IBM and thank you Coursera!

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por Victor d O

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Jan 09, 2019

I think we need in this module more pratical assignments.

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por Dmitry B

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Jan 11, 2019

This course is packed with info on different deep learning techniques and libraries. Not all of them can be found in exercises though.